{"title":"Evaluation and Analysis of the Implementation Effects in Practical-Course Blended Learning Based on Virtual Reality Technology","authors":"Man Peng","doi":"10.3991/ijet.v18i15.42379","DOIUrl":null,"url":null,"abstract":"Practical-course blended learning based on virtual reality (VR) technology combines VR with traditional practical teaching, which provides students with a more diverse and personalized learning experience. The existing evaluation and analysis methods of teaching model implementation effects have shortcomings. Although VR technology plays an important role in practical-course blended learning, excessive reliance on technical means may lead to limitations in evaluation methods. Therefore, this study aimed to explore the evaluation and analysis of implementation effects of VR-based practical-course blended learning. Different types of teaching models were represented. A robust multi-target collaborative tracking method based on variational Bayesian inference was applied to track and evaluate the implementation effects of practical-course blended learning. The experimental results verified the effectiveness of the proposed method and explored the impact of different teaching models on the average scores and score stability of evaluation methods. Analysis results of score data showed that the assisted-teaching model improved the homework performance of students and the blended-learning model improved the performance of students in tests and final exams, while the complete teaching model performed more balanced in all aspects.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Emerging Technologies in Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/ijet.v18i15.42379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Practical-course blended learning based on virtual reality (VR) technology combines VR with traditional practical teaching, which provides students with a more diverse and personalized learning experience. The existing evaluation and analysis methods of teaching model implementation effects have shortcomings. Although VR technology plays an important role in practical-course blended learning, excessive reliance on technical means may lead to limitations in evaluation methods. Therefore, this study aimed to explore the evaluation and analysis of implementation effects of VR-based practical-course blended learning. Different types of teaching models were represented. A robust multi-target collaborative tracking method based on variational Bayesian inference was applied to track and evaluate the implementation effects of practical-course blended learning. The experimental results verified the effectiveness of the proposed method and explored the impact of different teaching models on the average scores and score stability of evaluation methods. Analysis results of score data showed that the assisted-teaching model improved the homework performance of students and the blended-learning model improved the performance of students in tests and final exams, while the complete teaching model performed more balanced in all aspects.
期刊介绍:
This interdisciplinary journal focuses on the exchange of relevant trends and research results and presents practical experiences gained while developing and testing elements of technology enhanced learning. It bridges the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions. Fields of interest include, but are not limited to: -Software / Distributed Systems -Knowledge Management -Semantic Web -MashUp Technologies -Platforms and Content Authoring -New Learning Models and Applications -Pedagogical and Psychological Issues -Trust / Security -Internet Applications -Networked Tools -Mobile / wireless -Electronics -Visualisation -Bio- / Neuroinformatics -Language /Speech -Collaboration Tools / Collaborative Networks